IEEE Access (Jan 2023)

A Novel Pseudonym Changing Scheme for Location Privacy Preservation in Sparse Traffic Areas

  • Ahsan Hayat,
  • Zainab Iftikhar,
  • Majid Iqbal Khan,
  • Abolfazl Mehbodniya,
  • Julian L. Webber,
  • Sarmad Hanif

DOI
https://doi.org/10.1109/ACCESS.2023.3303846
Journal volume & issue
Vol. 11
pp. 89974 – 89985

Abstract

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A large number of schemes have been proposed to deal with location privacy preservation in Vehicular Ad Hoc Networks (VANETs). One of the most popular ways to preserve location privacy is pseudonym changing, which includes mix-zone, silent zone, mix-context zone and trigger-based schemes. These schemes rely on changing pseudonyms after specific intervals to preserve location privacy of vehicles. Since pseudonym changing schemes are efficient in areas where traffic is dense, most of the pseudonym changing schemes require vehicles to be a part of dense traffic in order to change a pseudonym. Although pseudonym changing schemes are efficient in terms of location privacy preservation, a huge drawback is that these schemes are best suitable in dense traffic areas. Another drawback is that these schemes do not prevent from colluding attacks. In this paper, we propose a scheme, called LPSA (Location Privacy in Sparse Areas) to overcome this limitation. We modify the pseudonym changing scheme so as to preserve location privacy irrespective of the traffic density. This makes LPSA suitable for both dense and sparse traffic areas. For location privacy preservation in dense areas, we utilize pseudonym changing in mix-context zones. To preserve location privacy in sparse areas, we modify pseudonym changing scheme. We use differential privacy to preserve privacy of the data shared by the vehicles. Noise is added in raw beacon message attributes using Local Differential Privacy (LDP) to get perturbed messages. Multiple perturbed messages are transmitted to confuse an adversary in sparse traffic areas. LPSA also provides protection against colluding attacks. Our results show that LPSA provides better traceability, average anonymity set size, pseudonym change per trace and average confusion in both sparse and dense traffic areas as compared to the recent literature.

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